Baidu, DuckDuckGo, Google, Quant, Searx, Yandex…
Search engines have unusual names, and people all around the world use them these days for unusual things. Some of my teacher colleagues tell me that many learners of English now use search engines instead of dictionaries to find out what words mean. Actually, most search engines offer integrated dictionaries as part of their service. All you need to do is use the “define:” operator followed by the word you’d like explained.
Here’s an example, using Microsoft’s search engine Bing. If I type “define: medical” into Bing, it tells me that “medical” is an adjective that means “of or relating to the science of medicine, or to the treatment of illness and injuries”. There’s also an audio file that gives the pronunciation of the word and an example of its use: “the medical profession”. All of this is “powered by Oxford Dictionaries”, says Bing, and if you want the results in Arabic or Urdu, Bing Translator will provide just that.
Now, if I do the same for “informatics”, I learn from Bing that it’s a noun that means “information science”, and if I then tell Bing “define: medical informatics”, I find out that it is “the study of the design, development, adoption and application of IT-based innovations in healthcare services delivery, management and planning”.
I first heard of medical informatics when one of the technology newsletters I read mentioned that 100 students had started a bachelor’s degree in “human medicine” at ETH in Zurich. ETH is a famous science, technology and engineering university and by including medical informatics in its new human medicine course, it is taking an important step towards bringing medical education and machine learning closer together.
The long-term thinking in Switzerland is that this will help produce a new generation of doctors who recognize the importance of collecting, protecting and understanding health data.
The human face, as it were, of data- driven Swiss human medicine is Dr Kar- sten Borgwardt. The 36-year-old studied computer science, with a minor in biology, in Munich and then completed a master’s degree in biology at Oxford University. Today, he heads the Machine Learning & Computational Biology Lab at ETH.
“Big data analysis and biomedical research meet in our lab: we develop data mining algorithms to detectpatterns and statistical dependencies in large datasets from biology and medicine,” says Borgwardt’s ETH web page.
The banking business is still big in Switzerland, but health tech is set to play an increasingly important role in the country’s economy. The global race is on to develop the strategies needed to find the information that can be used for precise and personalized therapies. And with its “Big Data” national research programme, the Swiss National Science Foundation has provided funding “for the effective and appropriate use of big data” in a range of industries, including healthcare.
One of Karsten Borgwardt’s goals is to determine the risk of contracting dangerous diseases based on a person’s genome. We are a long way from being able to do this, however, because diseases such as cancer may be caused by interactions among the three billionbase pairs in human DNA. With the help of their algorithms, Borgwardt and his team hope to find some answers, but it’s not going to be as easy as telling a search engine “define: success”. Well, not yet.